bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model

Various algorithms for segmentation of 2D and 3D images, such
as computed tomography and satellite remote sensing. This package implements
Bayesian image analysis using the hidden Potts model with external field
prior of <doi:10.1016/j.csda.2014.12.001>.
Latent labels are sampled using chequerboard updating or Swendsen-Wang.
Algorithms for the smoothing parameter include pseudolikelihood, path sampling,
the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC),
and Bayesian indirect likelihood (BIL). Refer to <doi:10.1007/s11222-014-9525-6>
and <arXiv:1503.08066> for further details.